A color classification algorithm for color images

  • Shoji Tominaga
Image Segmentation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 301)


We describe a color classification algorithm that partitions color image data into a set of uniform color regions. The algorithm uses a recursive method to detect clusters of color data. The algorithm can be divided into two main steps. First, we map the device dependent image data into an approximately uniform perceptual color space. Second, we apply a recursive histogram analysis to the data represented in this perceptually uniform space. The histogram analysis is designed to identify the spatial subregions within the image that correspond to a uniform color. Once a region has been identified, the corresponding data are removed and the histogram analysis is repeated on the remaining data set. The performance of the algorithm is discussed with respect to a test image.


Color Space Histogram Analysis Color Specification Segmented Region Color Classification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1988

Authors and Affiliations

  • Shoji Tominaga
    • 1
  1. 1.Department of PsychologyStanford UniversityStanfordUSA

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